US8890981B2 - Method and apparatus for eliminating crosstalk amount included in an output signal - Google Patents

Method and apparatus for eliminating crosstalk amount included in an output signal Download PDF

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US8890981B2
US8890981B2 US13/058,777 US201013058777A US8890981B2 US 8890981 B2 US8890981 B2 US 8890981B2 US 201013058777 A US201013058777 A US 201013058777A US 8890981 B2 US8890981 B2 US 8890981B2
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crosstalk
pixel
amount
corrected
correction coefficient
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US20110134288A1 (en
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Masanori Kasai
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Sony Semiconductor Solutions Corp
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N9/00—Details of colour television systems
    • H04N9/64—Circuits for processing colour signals
    • H04N9/646—Circuits for processing colour signals for image enhancement, e.g. vertical detail restoration, cross-colour elimination, contour correction, chrominance trapping filters
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N25/00—Circuitry of solid-state image sensors [SSIS]; Control thereof
    • H04N25/60—Noise processing, e.g. detecting, correcting, reducing or removing noise
    • H04N25/62—Detection or reduction of noise due to excess charges produced by the exposure, e.g. smear, blooming, ghost image, crosstalk or leakage between pixels
    • H04N25/625—Detection or reduction of noise due to excess charges produced by the exposure, e.g. smear, blooming, ghost image, crosstalk or leakage between pixels for the control of smear
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
    • H04N23/10—Cameras or camera modules comprising electronic image sensors; Control thereof for generating image signals from different wavelengths
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N17/00—Diagnosis, testing or measuring for television systems or their details
    • H04N17/002—Diagnosis, testing or measuring for television systems or their details for television cameras
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
    • H04N23/80—Camera processing pipelines; Components thereof
    • H04N23/84—Camera processing pipelines; Components thereof for processing colour signals
    • H04N23/843—Demosaicing, e.g. interpolating colour pixel values
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N25/00—Circuitry of solid-state image sensors [SSIS]; Control thereof
    • H04N25/10—Circuitry of solid-state image sensors [SSIS]; Control thereof for transforming different wavelengths into image signals
    • H04N25/11—Arrangement of colour filter arrays [CFA]; Filter mosaics
    • H04N25/13—Arrangement of colour filter arrays [CFA]; Filter mosaics characterised by the spectral characteristics of the filter elements
    • H04N25/133—Arrangement of colour filter arrays [CFA]; Filter mosaics characterised by the spectral characteristics of the filter elements including elements passing panchromatic light, e.g. filters passing white light
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N25/00—Circuitry of solid-state image sensors [SSIS]; Control thereof
    • H04N25/10—Circuitry of solid-state image sensors [SSIS]; Control thereof for transforming different wavelengths into image signals
    • H04N25/11—Arrangement of colour filter arrays [CFA]; Filter mosaics
    • H04N25/13—Arrangement of colour filter arrays [CFA]; Filter mosaics characterised by the spectral characteristics of the filter elements
    • H04N25/135—Arrangement of colour filter arrays [CFA]; Filter mosaics characterised by the spectral characteristics of the filter elements based on four or more different wavelength filter elements
    • H04N25/136—Arrangement of colour filter arrays [CFA]; Filter mosaics characterised by the spectral characteristics of the filter elements based on four or more different wavelength filter elements using complementary colours
    • H04N9/045—

Definitions

  • the present invention relates to an image processing device and image processing method, an imaging apparatus, and a computer program, wherein output signals from an imaging device having a color filter with color coding are processed, an particularly relates to an image processing device and image processing method, an imaging apparatus, and a computer program, wherein output signals from an imaging device using white pixels in color coding are processed.
  • the camera has a long history as a means to record visual information.
  • digital cameras which perform digital encoding of images captured with a solid state imaging device such as a CCD (Charge Coupled Device) or CMOS (Complementary Mental-Oxide Semiconductor) or the like has become widespread, replacing silver-salt cameras which take pictures using film or photosensitive plates.
  • Digital cameras are advantageous in that images subjected to digital encoding are stored in memory and image processing and image management can be performed by computer, and further, that there is no problem of the life expectancy of film.
  • Either imaging devices of CCD and CMOS are configured with an arrangement wherein two-dimensionally arrayed pixels (photodiodes) use photoelectric effect to convert light into electric charge.
  • the surface of each pixel has a color pixel of one of three colors of R (red), green (G), blue (B), for example, and signal charge corresponding to the amount of incident light passing through each color filter is accumulated in each pixel.
  • the color filters are band-pass filters which pass light of a predetermined wavelength. Signal charges according to the amount of incident light of each color are read out from each pixel, and the color of incident light at each pixel position can be reproduced from the amount of signal charge of each of the three colors.
  • FIG. 12A illustrates a Bayer array which is a representative filter array of primary colors.
  • FIG. 12B illustrates an example of a filter array including white pixels.
  • R represents Red (red) color filters
  • G represents Green (green) color filters
  • B represents Blue (blue) color filters
  • W represents White (white) color filters, respectively.
  • white pixels are introduced between the RGB primary color system color filters in an intermittent manner.
  • crosstalk optical and electrical crosstalk, i.e., color mixing (hereinafter referred to simply as “crosstalk”) will occur between adjacent.
  • Factors of crosstalk include leaking of light which should be collected at the adjacent pixel, electrons leaking between pixels, and so forth.
  • Crosstalk leads to deterioration in resolution and loss of color information, and accordingly needs to be corrected.
  • crosstalk is not a problem unique to imaging devices using color filters including white pixels in the array.
  • a greater amount of light leaks from white pixels so deterioration of images due to crosstalk is more marked as compared to imaging devices using color filters not including white pixels in the array.
  • the amount of crosstalk varies depending on optical conditions such as individual micro-lenses. This is because crosstalk is dependent on the incident angle. Accordingly, the amount of crosstalk differs depending on the position of the pixels on the chip face. Also, the depth of penetration into the silicon (Si) substrate configuring the imaging device differs depending on the wavelength of the light, so the amount of crosstalk also changes depending on the color temperature of the light source at the time of shooting.
  • a signal processing method which handles change in crosstalk owing to optical conditions, by performing corresponding processing as to signals of a pixel of interest using signals of each of multiple surrounding pixels adjacent to a pixel of interest of the imaging device, and correction parameters set independently for each of the signals (e.g., see PTL 2).
  • the values of the correction parameters are set in accordance with the aperture of the diaphragm included in the optical system guiding light from the subject to the imaging device. That is to say, the lens to be used is already decided, the amount of crosstalk according to the lens has been measured beforehand, and correction is performed as to this. Accordingly, correction of the amount of crosstalk is difficult with a situation where lens information is unknown, such as with exchangeable lenses wherein the user can freely exchange lenses.
  • an image processing device including:
  • a crosstalk amount calculating unit for calculating an evaluation value of crosstalk amount included in an output signal from a pixel to be corrected in an imaging device
  • a crosstalk correction coefficient calculating unit for calculating a crosstalk correction coefficient based on the evaluation value output from the crosstalk amount calculating unit
  • a crosstalk correcting unit for eliminating crosstalk amount included in an output signal of the pixel to be corrected, using the crosstalk correction coefficient.
  • the crosstalk amount calculating unit of the image processing device is configured to calculate the evaluation value of crosstalk amount included in an output signal of the pixel to be corrected, based on output signals from the imaging device.
  • the crosstalk amount calculating unit of the image processing device is configured to calculate the evaluation value of crosstalk amount included in an output signal of the pixel to be corrected, based on the relation of output signals between adjacent pixels.
  • the imaging device is configured to use color coding including white pixels.
  • Crosstalk is not a problem unique to imaging devices using color filters including white pixels in the array, but a greater amount of light leaks from white pixels, so deterioration of images due to crosstalk is more marked as compared to imaging devices using color filters not including white pixels in the array.
  • the crosstalk amount calculating unit may be configured to calculate an evaluation value for crosstalk amount included in an output signal of a pixel to be corrected, based on the proportion of the sum of the signal amount of the pixels other than white, as to the signal amount of white pixels.
  • the crosstalk amount calculating unit may be configured to calculate an evaluation value for the relative amount of crosstalk included in an output signal of a pixel to be corrected, based on the proportion of the sum of values obtained by multiplying the signal amounts of each of RGB pixels by respective predetermined coefficients ( ⁇ , ⁇ , ⁇ ), as to a value obtained by multiplying the signal amount of white pixels by a predetermined coefficient ( ⁇ ).
  • the crosstalk amount calculating unit a is configured to calculate an evaluation value of crosstalk amount, with N ⁇ N pixels as an increment of processing (where N is a positive integer).
  • the image processing device is configured further including memory for storing evaluation values which the crosstalk amount calculating unit has calculated in increments of processing, wherein the crosstalk correction coefficient calculating unit and the crosstalk correction unit respectively perform calculation of correction coefficients and correction of crosstalk, using the evaluation values calculated using previous frames saved in the memory.
  • the crosstalk correction coefficient calculating unit of the image processing device is configured to calculate beforehand a relational expression between the evaluation value of crosstalk amount calculated by the crosstalk amount calculating unit, and correction coefficients, and at the time of an evaluation value output from the crosstalk amount calculating unit being output, references the relational expression and calculates a correction coefficient corresponding to the evaluation value.
  • the crosstalk correction unit of the image processing device is configured to subtract, from an output signal of a pixel to be corrected, a value obtained by multiplying the output signal of a pixel adjacent to the pixel to be corrected by the correction coefficient, thereby eliminating amount of crosstalk.
  • the imaging device of the image processing device has disposed a plurality of arrays for calculating evaluation values including white pixels, in an array not including white pixels.
  • the crosstalk amount calculating unit of the image processing device is configured to use each of the arrays for calculating evaluation values to calculate evaluation values of crosstalk amount occurring at relevant positions.
  • the crosstalk correction coefficient calculating unit is configured to calculate a crosstalk correction coefficient based on the evaluation value output from the crosstalk amount calculating unit, for each position where an array for calculating evaluation values is disposed.
  • the crosstalk correcting unit is configured to perform correction of crosstalk using a relevant coefficient, within an array for calculating evaluation values, and performs correction of crosstalk using a crosstalk correction coefficient determined based on an evaluation value of crosstalk amount obtained from a nearby array for calculating evaluation values, in a region outside of an array for calculating evaluation values.
  • an invention of the present application is an image processing method including:
  • a crosstalk amount calculating step for calculating an evaluation value of crosstalk amount included in an output signal from a pixel to be corrected in an imaging device
  • a crosstalk correction coefficient calculating step for calculating a crosstalk correction coefficient based on the evaluation value output in the crosstalk amount calculating step
  • a crosstalk correcting step for eliminating crosstalk amount included in an output signal of the pixel to be corrected, using the crosstalk correction coefficient.
  • an imaging apparatus including:
  • an imaging device including a color coding color filter
  • a signal processing unit for processing output signals of the imaging device
  • the signal processing unit includes
  • an invention of the present application is a computer program described in a computer-readable format so as to execute processing of output signals from an imaging device having a color coding color filter, the computer program causing the computer to function as:
  • a crosstalk amount calculating unit for calculating an evaluation value of crosstalk amount included in an output signal from a pixel to be corrected in the imaging device
  • a crosstalk correction coefficient calculating unit for calculating a crosstalk correction coefficient based on the evaluation value output from the crosstalk amount calculating unit
  • a crosstalk correcting unit for eliminating crosstalk amount included in an output signal of the pixel to be corrected, using the crosstalk correction coefficient.
  • the computer program of the present application defines a computer program described in a computer-readable format so as to realize predetermined processing on a computer.
  • cooperative effects are manifested on the computer, whereby operation effects the same as with the image processing device of the present application can be obtained.
  • an excellent image processing device and image processing method, imaging apparatus, and computer program wherein the crosstalk amount included in output signals of an imaging device using white pixels in color coding can be suitably corrected, even under conditions where optical conditions, such as the lens being used, are unknown, can be provided.
  • an evaluation value for telling the crosstalk amount can be calculated from the shooting data alone, and correction processing of crosstalk can be performed using correction coefficients applied to this evaluation value.
  • crosstalk amount is calculated based on output signals from the imaging device, so crosstalk correction can be performed even under conditions where optical conditions such as the lens being used are unknown, and also, crosstalk correction can be performed by digital signal processing.
  • an evaluation value of crosstalk amount at a pixel to be corrected can be calculated based on the proportion of the sum of the signal amount of adjacent RGB pixels as to the signal amount of white pixels, employing the fact that phenomena from the vertical direction and horizontal direction are dominant.
  • pixels of the same color within a processing increment have two or more outputs, so an average value of signal amount can be used for each color.
  • calculation of correction coefficients and crosstalk correction can be performed using evaluation values calculated using previous frames, so moving image processing can be handled.
  • correction coefficients can be calculated from evaluation values output from the crosstalk amount calculating unit, based on a relational expression calculated beforehand between crosstalk amount evaluation values and correction coefficients.
  • a value obtained by multiplying the output signal of a pixel adjacent to a pixel to be corrected is subtracted from the output signal of a pixel to be corrected, whereby amount of crosstalk can be eliminated.
  • the degree of crosstalk over the entire imaging device face can be known by evaluating each crosstalk amount using each array for calculating evaluation values.
  • Crosstalk can be suitably corrected by then determining a correction coefficient in each region based on the crosstalk amount evaluation value obtained from a nearby array for calculating evaluation value.
  • FIG. 1 is a diagram schematically illustrating the hardware configuration of an imaging apparatus 100 serving as an embodiment of the present invention.
  • FIG. 2 is a diagram illustrating a functional configuration for performing image signal processing for crosstalk correction.
  • FIG. 3A is a diagram illustrating an example of spectral properties of an imaging device 12 for each color pixel (degree of crosstalk small) (spectral properties 1 ).
  • FIG. 3B is a diagram illustrating an example of spectral properties of the imaging device 12 for each color pixel (degree of crosstalk medium) (spectral properties 2 ).
  • FIG. 3C is a diagram illustrating an example of spectral properties of the imaging device 12 for each color pixel (degree of crosstalk great) (spectral properties 3 ).
  • FIG. 4A is a diagram illustrating the way in which crosstalk occurs from the vertical direction and horizontal direction.
  • FIG. 4B is a diagram illustrating the way in which white signals mix into adjacent RGB signals in the color pixel array shown in FIG. 12B .
  • FIG. 4C is a diagram illustrating the way in which RGB signals mix into adjacent white signals in the color pixel array shown in FIG. 12B .
  • FIG. 5A is a diagram illustrating reflectance spectral properties of a blue patch (patch No. 13 ) in the Macbeth Color Checker chart.
  • FIG. 5B is a diagram illustrating reflectance spectral properties of a green patch (patch No. 14 ) in the Macbeth Color Checker chart.
  • FIG. 5C is a diagram illustrating reflectance spectral properties of a red patch (patch No. 15 ) in the Macbeth Color Checker chart.
  • FIG. 5D is a diagram illustrating reflectance spectral properties of a yellow patch (patch No. 16 ) in the Macbeth Color Checker chart.
  • FIG. 5E is a diagram illustrating reflectance spectral properties of a magenta patch (patch No. 17 ) in the Macbeth Color Checker chart.
  • FIG. 5F is a diagram illustrating reflectance spectral properties of a cyan patch (patch No. 18 ) in the Macbeth Color Checker chart.
  • FIG. 6A is a diagram illustrating the results of integrating the reflectance spectral properties of each Macbeth color path shown in FIG. 5A through FIG. 5F with spectral properties corresponding to the crosstalk amount for each color pixel of the imaging device 12 shown in FIG. 3A (spectral properties 1 ).
  • FIG. 6B is a diagram illustrating the results of integrating the reflectance spectral properties of each Macbeth color path shown in FIG. 5A through FIG. 5F with spectral properties corresponding to the crosstalk amount for each color pixel of the imaging device 12 shown in FIG. 3B (spectral properties 2 ).
  • FIG. 6C is a diagram illustrating the results of integrating the reflectance spectral properties of each Macbeth color path shown in FIG. 5A through FIG. 5F with spectral properties corresponding to the crosstalk amount for each color pixel of the imaging device 12 shown in FIG. 3C (spectral properties 3 ).
  • FIG. 7A is a diagram illustrating evaluation values obtained for each Macbeth color patch for the primary six colors, with regard to each spectral property according to the crosstalk amount ( FIG. 3A through FIG. 3C ).
  • FIG. 7B is a diagram illustrating evaluation values obtained for all Macbeth color patches, with regard to each spectral property according to the crosstalk amount ( FIG. 3A through FIG. 3C ).
  • FIG. 8 is a diagram for describing a common crosstalk correction processing method.
  • FIG. 9 is a diagram illustrating an example of a relational expression between crosstalk amount evaluation values (K) and correction coefficients.
  • FIG. 10 is a diagram illustrating an example of a region (block) for calculating correction coefficients with magnitude of a certain degree.
  • FIG. 11 is a diagram illustrating memory 4 for holding the evaluation value (K) calculated at a crosstalk correction calculating unit 1 .
  • FIG. 12A is a diagram illustrating a Bayer array which is a representative filter array for a primary color system.
  • FIG. 12B is a diagram illustrating an example of a filter array including white pixels.
  • FIG. 13A is a diagram illustrating another example of a filter array including white pixels.
  • FIG. 13B is a diagram illustrating another example of a filter array including white pixels.
  • FIG. 13C is a diagram illustrating another example of a filter array using a complementary color filter.
  • FIG. 14 is a diagram illustrating an example of a filter array wherein arrays including white pixels such as shown in FIG. 12B , are scattered throughout a Bayer array not including white pixels (see fog. 12 A).
  • FIG. 15 is a diagram schematically illustrating the way in which multiple evaluation value calculating arrays such as shown in FIG. 12B are disposed on an imaging device face based on the Bayer array shown in FIG. 12A .
  • FIG. 16 is a diagram schematically illustrating the way in which multiple evaluation value calculating arrays such as shown in FIG. 12B are disposed on an imaging device face based on the Bayer array shown in FIG. 12A .
  • FIG. 1 schematically illustrates the hardware configuration of an imaging apparatus 10 serving as an embodiment of the present invention.
  • imaging apparatus includes imaging devices, camera modules including an optical system for imaging image light on an imaging face (light-receiving face) of the imaging device and a signal processing circuit for the imaging device, camera apparatuses such as digital still cameras and video cameras in which the camera module is implemented, and electronic equipment such as cellular phones.
  • image light from a subject is imaged on the imaging face of an imaging device 12 by an optical system, an imaging lens 11 for example.
  • an imaging device is used which is formed by a great number pixels including photoelectric converting devices being arrayed two-dimensionally in matrix fashion, and a color filter including color components of a primary color for creating luminance components, and other color components, are disposed on the surface of the pixels.
  • a color filter is a band-pass filter which passes light of predetermined wavelengths.
  • the imaging device having a color filter may be any of a charge-transfer imaging device of which a CCD is representative, an X-Y address imaging device of which a MOS is representative, or the like.
  • the color filter includes green (G) for example as a color components serving as a primary component for creating a luminance (Y) component, and red (R) and blue (B) for example as other color components, respectively, and performs color coding so as to reproduce color of incident light at each pixel position.
  • G green
  • R red
  • B blue
  • color coding of an array including white pixels is performed for the color filter, in order to realize high sensitivity and so forth.
  • the array of pixels is not restricted to that shown in FIG. 12B . Note that an arrangement may be made wherein as color components serving as a primary component for creating the Y component, white, cyan, yellow, or the like are used, and magenta, cyan, yellow, or the like, are used for other color components.
  • the imaging device 12 With the imaging device 12 , of the incident image light, only light of each color component passes through the color filters and is input to each pixel. The light that has been input to each pixel is subjected to photoelectric conversion by photoelectric converters such as photodiodes. This is then read out from each pixel as analog image signals, converted into digital image signals at an A/D converter (ADC) 13 , and input to a camera signal processing circuit 14 which is equivalent to the image processing device according to the present invention.
  • ADC A/D converter
  • the camera signal processing circuit 14 is configured of an optical system correcting circuit 21 , a WB (white balance) circuit 22 , an interpolation processing circuit 23 , a gamma ( ⁇ ) correction circuit 24 , a Y (brightness) signal processing circuit 25 , a C (chroma) signal processing circuit 26 , a band limiting LPF (low-pass filter) 27 , a thinning out circuit 28 , and so forth.
  • the optical system correcting circuit 21 performs correction of the imaging device 12 and optical system, such as digital clamping to match the black level with the digital image signals input to the camera signal processing circuit 14 , defect correction for correcting defects of the imaging device 12 , shading correction for correcting light falloff at edges for the imaging lens 11 , and so forth.
  • the color filter used with the imaging device according to the present embodiment includes white pixels, so the problem of crosstalk becomes pronounced, and accordingly there is the need to perform correction thereof. While the point of performing calculation and correction of crosstalk amount at the stage of digital signal processing is a main feature of the present invention, the function thereof cam be implemented within the optical system correcting circuit 21 . Details of calculation and correction of crosstalk amount will be described later.
  • the WB circuit 22 subjects image signals which have passed through the optical system correcting circuit 21 to processing for adjusting the white balance, such that RGB is the same as to a white subject.
  • the interpolation processing circuit 23 creates pixels with different spatial phases by interpolation, i.e., creates three planes from RGB signals with spatially shifted phases (RGB signals at the same spatial position).
  • the gamma ( ⁇ ) correction circuit 24 subjects the RGB signals at the same spatial position to gamma correction, and then supplies to the Y-signal processing circuit 25 and C-signal processing circuit 26 .
  • Gamma correction is processing for applying a predetermined gain to each of the R, G, and B color signals output from the WB circuit 22 , such that the photoelectric conversion properties of the entire system, including the imaging device 12 and downstream image reproducing means and so forth, are 1 , so as to correctly express the color tone of the subject.
  • the Y-signal processing circuit 25 creates brightness (Y) signals from the R, G, and B color signals
  • the C-signal processing circuit 26 creates Cr (R ⁇ Y) and Cb (B ⁇ Y) from the R, G, and B color signals.
  • the band limiting LPF 27 is a filter wherein the cutoff frequency f c is 1 ⁇ 8 of the sampling frequency f s for example, and drops the passing band for color difference signals Cr and Cb from (1 ⁇ 2) f s to (1 ⁇ 8) f s . However, this is output for TV signal format, and in the event that output is performed without band limitation, frequency signals of 1 ⁇ 8 f s or higher will be output as false color signals.
  • the thinning out circuit 28 performs thinning out of sampling of the color difference signals Cr and Cb.
  • FIG. 2 illustrates the functional configuration for performing image signal processing for crosstalk correction.
  • the image signal processing is configured of a crosstalk amount calculating unit 1 , a crosstalk correction coefficient calculating unit 2 , and a crosstalk correction unit 3 , and is implemented in the optical system correction circuit 21 .
  • the crosstalk amount calculating unit 1 will be described first.
  • the crosstalk amount calculating unit 1 performs quantification of the degree of crosstalk as the crosstalk amount, based on imaged data output from the imaging device 12 .
  • FIG. 3 illustrates examples of spectral properties for each color pixel of the imaging device 12 .
  • the degree of crosstalk increases in the order of FIG. 3A , FIG. 3B , and FIG. 3C .
  • Blue (B) is a filter which passes around 450 nanometers
  • Green (G) is a filter which passes around 550 nanometers
  • red (R) is a filter which passes around 650 nanometers.
  • white (W) pixels are the same as with a monochrome imaging device with no color filter.
  • the crosstalk amount increases, the output at frequency regions where there should be no sensitivity increases. For example, in FIG. 3C , the output and the band of 550 to 650 nanometers has increased at the waveform for blue (B_ 3 ) pixels, due to crosstalk.
  • Crosstalk can be generally divided into two types, i.e., one where white signals are mixed into adjacent RGB signals, as shown in FIG. 4B , and one where RGB signals are mixed into adjacent white signals, as shown in FIG. 4C .
  • the method thereof is to calculate the proportion between the sum of the signal amount of each of the signals, and the signal amount of the white signals (described later).
  • a “Macbeth Color Checker (Macbeth Color chart)” is used for evaluating color reproducibility.
  • “Color Imaging”, edited by the Color Science Association of Japan (pp 29-33) describes that spectral sensitivity, tone reproduction, and the three primary colors are factors governing color reproducibility, and that a method is generally used in which these factors are not separately evaluated in color reproducibility evaluation but rather the color reproducibility finally obtained is evaluated, and that as for the evaluation method, a standard color chart is input as an image and the output reproduced colors are compared with the colors of the original color chart by spectral reflectivity (transmissivity), and that the Macbeth Color chart is widely used as the color chart.
  • Transmissivity spectral reflectivity
  • a Macbeth Color chart is made up of 24 colors including 6 shades of gray. The surface of each color chart is matte, and is of a size of 45 mm ⁇ 45 mm.
  • This literature lists the reflective spectral properties (spectral reflectivity) of the Macbeth Color chart as appendix Tables A.1 and A.2. Description will be made below using this spectral data.
  • FIGS. 5A through 5F illustrate the reflective spectral properties of each patch of blue (patch No. 13 ), green (patch No. 14 ), red (patch No. 15 ), yellow (patch No. 16 ), magenta (patch No. 17 ), and cyan (patch No. 18 ) in the Macbeth Color Checker chart. Note that the reason that only the above six colors of the 24 colors in the Macbeth Color chart are used is due to the fact that these six colors are the primary color components used in many color imaging systems.
  • FIG. 6A through FIG. 6C illustrate the results of integrating the reflectance spectral properties of each Macbeth color patch shown in FIG. 5A through FIG. 5F with the spectral properties of each color pixel of the imaging device shown in FIG. 3A through FIG. 3C , respectively.
  • FIG. 6A through FIG. 6C are equivalent to output corresponding to the crosstalk amount of each color pixel of the imaging device 12 .
  • An evaluation value (K) for evaluation the crosstalk amount can be calculated using the following Expression (1) for example, based on the output (see FIG. 6A through FIG. 6C ) for each of the color pixels (R, G, B, W) of the imaging device 12 obtained from the spectral properties (see FIG. 3A through FIG. 3C ) according to the crosstalk amount of each color pixel of the imaging device 12 .
  • R, G, b, and W are output values of each of the color pixels (see FIG. 6A through 6C ), ⁇ , ⁇ , ⁇ , and ⁇ are arbitrary coefficients, and the evaluation value (K) is equivalent to the result of calculating the proportion of the sum of output of each of the RGB color pixels as to the output for the white pixels.
  • This expression is based on the fact that with the color coding shown in FIG. 12B for example, crosstalk can be generally divided into two types; one where white signals are mixed into adjacent RGB signals, as shown in FIG. 4B , and one where RGB signals are mixed into adjacent white signals, as shown in FIG. 4C (described above).
  • FIG. 7A illustrates evaluation values obtained for each Macbeth color patch, with regard to each spectral property corresponding to crosstalk amount ( FIG. 3A through FIG. 3C ). Also, the average and standard deviation for the evaluation values K_ 1 , K_ 2 , and K_ 3 obtained for each of the spectral properties 1 through 3 over all six color patches have been compiled in the following table.
  • the evaluation value (K) is generally constant, regardless of the reflectance properties of the subject (each color). This means that the evaluation value (K) calculated from the above Expression (1) is capable of being used in evaluating crosstalk amount.
  • the coefficients ⁇ , ⁇ , ⁇ , and ⁇ are optimized such that the evaluation value (K) is constant in ideal spectral properties where the crosstalk amount is small, as shown in FIG. 3A , for example. In reality, an approximation method such as least square or the like is used. The obtained value is used as to other spectral properties such as in FIG. 3B and FIG. 3C , as well.
  • FIG. 7B illustrates the results. Also, the average and standard deviation for the evaluation values K_ 1 , K_ 2 , and K_ 3 obtained for each of the spectral properties 1 through 3 over all 24 color patches have been compiled in the following table. Since the evaluation value (K) is generally constant regardless of the reflectance properties of the subject (each color), it can be reconfirmed that the evaluation value (K) calculated from the above Expression (1) is capable of being used in evaluating crosstalk amount.
  • relative change in crosstalk amount can be detected by calculating the evaluation value (K) using output signals from the imaging device 12 using color coding in which white pixels are added to RGB pixels. That is to say, the degree of crosstalk amount can be detected from the output signals of the imaging device 12 alone, with no need to measure the crosstalk amount within the chip beforehand as has been conventional done (e.g., see PTL 2). Accordingly, the degree of crosstalk can be quantized at the state of digital signal processing, even in a situation wherein optical conditions, such as the lens to be used, are unknown.
  • the crosstalk amount calculating unit 1 output signals of pixels of all colors including the white pixels are necessary, as can be understood from the above Expression (1). Accordingly, in the case of calculating the evaluation value (K) in real time as to the imaging device 12 having a filter array such as shown in FIG. 12B , the value of around 4 ⁇ 4 pixels is preferably handled as the minimum increment. Pixels of the same color within a processing increment have two or more outputs, so the average value of signal amount is preferably used to calculate the above Expression (1).
  • crosstalk correction coefficient calculating unit 2 a crosstalk correction coefficient corresponding to the current crosstalk amount is calculated from the crosstalk amount output from the crosstalk amount calculating unit 1 and a relational expression between the crosstalk correction coefficient and crosstalk amount obtained beforehand.
  • S_crct represents the signal after correction
  • S represents the signal before correction
  • in side the parentheses are the coordinate positions, respectively.
  • (i, j) is one coordinates of the pixel to be corrected.
  • a, b, c, and d are correction coefficients as to adjacent pixels above, left, right, and below.
  • These a, b, c, and d are also values indicating the proportion of the adjacent pixel signals being crosstalk amount.
  • the correction coefficients a, b, c, and d may also be constant.
  • the crosstalk amount changes depending on the color temperature of the light source and optical conditions, and pixel position within the chip.
  • the correction coefficients also become greater.
  • shooting is performed beforehand changing the optical conditions, illumination color temperature conditions, and so froth, correction coefficients are calculated corresponding to the output of the crosstalk amount calculating unit 1 , i.e., to the evaluation value (K), and a relational expression such as shown in FIG. 9 is created.
  • the crosstalk correction coefficient calculating unit 2 upon the evaluation value (K) being output from the crosstalk amount calculating unit 1 , such a relational expression is referenced to obtain correction coefficients corresponding to the crosstalk amount in the area where shooting is actually being performed.
  • the crosstalk correction unit 3 As described above, with crosstalk, phenomena from the vertical direction and horizontal direction are dominant (see FIG. 4A ). Accordingly, with the crosstalk correction unit 3 , the signal of the pixel to be corrected is corrected by subtracting several tenths of the each of the signals of pixels adjacent vertically and horizontally, from the signal of the pixel to be corrected as crosstalk amount, following the correction expression shown in Expression (3) above for example, using the correction coefficients a, b, c, and d of the adjacent pixels calculated by the crosstalk correction coefficient calculating unit 2 .
  • FIG. 10 illustrates an example of a region (block) for calculating correction coefficients with a certain size.
  • each block is made up of 100 ⁇ 100 pixels, and one imaged image is made up of 6 ⁇ 8 blocks.
  • the evaluation value (K) is calculated following the above Expression (1). Then at the downstream crosstalk correction coefficient calculating unit 2 and crosstalk correction unit 3 , calculation of correction coefficients and pixel value correction processing are each performed.
  • memory 4 is provided to hold the evaluation value (K) calculated at the crosstalk amount calculating unit 1 .
  • the evaluation value (K) calculated at the crosstalk amount calculating unit 1 is then saved in the memory 4 , the evaluation value (K) is updated at a certain number of fixed intervals, and correction processing is performed on the imaged data.
  • 100 ⁇ 100 pixel blocks as the minimum increment, pixels of the same color within a processing increment have two or more outputs, so the average value of signal amount is preferably used to calculate the above Expression (4).
  • the number of pixels for calculating the evaluation value (K) is great, so even if there is much noise included in the data, an accurate evaluation value (K) can be obtained by averaging.
  • K average ⁇ ⁇ of ⁇ ⁇ ⁇ ⁇ ⁇ R + average ⁇ ⁇ of ⁇ ⁇ ⁇ ⁇ G + average ⁇ ⁇ of ⁇ ⁇ ⁇ ⁇ B average ⁇ ⁇ of ⁇ ⁇ ⁇ W ⁇ ⁇ ⁇ ( 4 )
  • this portion can be made inconspicuous by averaging the correction coefficients between the adjacent blocks.
  • the evaluation value for knowing crosstalk amount can be calculated from shooting data alone for arrays with different RGB arrays such as shown in FIG. 13A and FIG. 13B , or arrays using complementary color filters instead of primary color filters as shown in FIG. 13C , for example, in the same way as described above, and crosstalk correction processing can be performed using correction coefficients adapted to his evaluation value.
  • the present invention performs crosstalk correction of each pixel based on the evaluation results of crosstalk amount of white signals as to adjacent RGB signals (see FIG. 4B ) and crosstalk amount of RGB signals as to adjacent white signals (see FIG. 4C ), and in other words, white pixels are necessary for evaluating the crosstalk amount.
  • FIG. 14 illustrates an example of a filter array in which arrays including white pixels such as shown in FIG. 12B are scattered throughout a Bayer array not including white pixels (see FIG. 12A ).
  • crosstalk amount can be obtained from the array shown in FIG. 12B , and the crosstalk within the Bayer array can be corrected based on the crosstalk correction coefficients calculated using this crosstalk amount.
  • FIG. 15 schematically illustrates the way in which multiple evaluation calculating arrays such as shown in FIG. 12B are disposed on the imaging device face based on a Bayer array (see FIG. 12A ). Evaluating each crosstalk amount using each evaluation calculating array allows the degree of crosstalk to be known over the entire face of the imaging device. Crosstalk then can be adaptively corrected in each region by deciding crosstalk correction coefficients based on the evaluation value of the crosstalk amount obtained from a nearby evaluation calculating arrays.
  • crosstalk correction in each region can be performed using the above Expression (3).
  • crosstalk correction may be performed following the matrix operation shown in the following Expression (5), after performing interpolation processing at the interpolation processing circuit 23 (see FIG. 1 ).
  • FIG. 16 illustrates a configuration example of an imaging device for switching the interpolation method according to the pixel position. Note however, that only relevant parts are extracted and shown in this drawing. Interpolation processing can be performed at an interpolation circuit 23 A at pixel position following the Bayer array, and switched to interpolation processing at the interpolation circuit 23 for pixel positions for the evaluation value calculation arrays (see FIG. 12B ).
  • the present invention has been described in detail with reference to a particular embodiment, it is self-evident that one of ordinary skill in the art can make modifications and substitutions to the embodiment without departing from the essence of the present invention.
  • the present invention can be applied to, for example, a camera apparatus such as a digital still camera or video camera, various types of electronic equipment in which a camera module is implemented, such as cellular telephones, and so forth.
  • the evaluation value for knowing crosstalk amount can be calculated from shooting data alone for arrays with different RGB arrays such as shown in FIG. 13A and FIG. 13B , or arrays using complementary color filters instead of primary color filters as shown in FIG. 13C , for example, in the same way as described above, and crosstalk correction processing can be performed using correction coefficients adapted to this evaluation value.

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